摘要
衡量光伏发电的置信容量是大规模光伏电站接入电网时需要考虑的问题之一。以光伏发电接入后系统可以减少的发电容量来评估光伏发电的置信容量,建立了考虑不同天气类型概率、最大辐射强度、云遮波动以及温度系数波动的年光伏出力波动模型。提出了基于序贯蒙特卡罗仿真的电力系统发电可靠性的计算方法,并以光伏发电接入前后的系统电力不足期望(loss of load expectation,LOLE)为基础,建立了目标函数,并用粒子群优化算法搜索光伏发电接入后系统的常规机组组合,使系统的可靠性水平与光伏发电接入前保持一致。某标准算例的仿真计算验证了上述模型和方法的正确性和有效性。
To evaluate the capacity credit of photovoltaic（PV） generation is one of urgent problems to be considered when large-scale PV station is connected to traditional power grid.The capacity credit of PV generation is evaluated by the generation capacity that could be reduced in traditional power grid after the grid-connection of PV station.For this purpose,a new method for evaluating the capacity credit of PV generation is proposed.Firstly,an annual output fluctuating model of PV generation,in which the occurrence probabilities of different weather types,the maximum proportions of solar radiation under various whether conditions,the fluctuation radiation range due to clouds mask and the temperature coefficient random variation range are taken into account,is built;secondly,based on sequential Monte-Carlo simulation,a method to calculate generation reliability of power grid is put forward and its objective function is established based on the loss of load expectation（LOLE） before and after the grid-connection of PV station,and then the particle swarm optimization is utilized to search optimal combination of traditional generation sets to make the generation reliability level of power grid conforming with that before the grid-connection of PV station.Both correctness and effectiveness of the proposed model and algorithm are verified by simulation results of IEEE-RTS79 system.
出处
《电网技术》
EI
CSCD
北大核心
2012年第9期31-35,共5页
Power System Technology
关键词
光伏发电
容量置信度
发电可靠性
序贯蒙特卡罗法
粒子群优化
photovoltaic （PV）
capacity credit
generationreliability
sequential Monte-Carlo
particle swarm optimization
